Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "22"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 22 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 27 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 27 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 22, Node N06:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460010 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.561086 -0.135987 0.357510 -0.240208 0.185328 0.719420 -0.464638 -1.090686 0.5538 0.5635 0.3526 nan nan
2460009 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.937263 -0.594711 -0.004548 -0.765916 0.091784 1.944427 -0.677834 -0.805088 0.5581 0.5676 0.3580 nan nan
2460008 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.750383 -0.263718 0.270010 -0.326683 0.543325 0.540591 -0.185580 -0.732421 0.6083 0.6215 0.3242 nan nan
2460007 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.708822 -0.345084 0.033926 -0.299280 0.544884 0.669080 -0.250131 -1.217716 0.5645 0.5771 0.3452 nan nan
2459999 not_connected 0.00% 89.89% 86.05% 0.00% - - nan nan nan nan nan nan nan nan 0.1451 0.1729 0.0762 nan nan
2459998 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.594682 -0.248917 0.099047 -0.149850 0.678352 1.938959 -0.779232 -0.855589 0.5612 0.5787 0.3715 nan nan
2459997 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.566261 -0.417360 0.274532 -0.173963 0.755146 1.355975 -0.817711 -1.698982 0.5858 0.6032 0.3788 nan nan
2459996 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.575529 -0.276205 -0.016333 -0.572053 -0.263426 1.342623 -0.455168 -0.258556 0.5890 0.6031 0.3898 nan nan
2459995 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.492459 -0.451692 0.221525 -0.320584 1.242681 3.246640 -0.659600 -0.751589 0.5872 0.6029 0.3775 nan nan
2459994 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.602105 -0.448001 0.297346 -0.156930 0.845497 1.456776 -0.654729 -1.274482 0.5790 0.5941 0.3735 nan nan
2459993 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.358242 -0.155434 0.663540 0.127999 0.802389 1.617301 -0.774736 -1.133995 0.5721 0.6053 0.3848 nan nan
2459991 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.445465 -0.195997 0.579395 0.191527 0.663453 0.975016 -0.447933 -1.098665 0.5783 0.5881 0.3790 nan nan
2459990 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.278421 -0.018790 0.590227 0.327297 0.794733 1.338597 -0.098282 -1.021941 0.5828 0.5951 0.3790 nan nan
2459989 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.344197 -0.135343 0.694975 0.237714 0.835288 0.930089 -0.670746 -1.239893 0.5779 0.5937 0.3814 nan nan
2459988 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.413643 0.080699 0.532728 0.322872 0.814273 1.471286 -0.401942 -0.815043 0.5599 0.5748 0.3644 nan nan
2459987 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.571782 -0.410804 0.350710 -0.107153 0.495137 0.856874 -0.227010 -0.679352 0.5845 0.5990 0.3680 nan nan
2459986 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.442346 -0.075910 0.356695 0.121935 1.374378 1.951805 0.097330 -0.941613 0.5928 0.6129 0.3389 nan nan
2459985 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.744239 -0.402051 0.122991 -0.261942 0.805063 1.259608 -0.253812 -1.214986 0.5759 0.5896 0.3734 nan nan
2459984 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.961198 -0.728946 0.047846 -0.361253 0.512134 -0.312134 0.935849 0.236597 0.5808 0.5966 0.3466 nan nan
2459983 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.611768 -0.307349 0.435144 0.194522 0.544273 1.500342 -0.035795 -0.773726 0.6104 0.6360 0.3083 nan nan
2459982 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.952877 -0.003960 -0.063595 -0.257072 -0.782483 -0.286629 -0.447041 -0.577362 0.6377 0.6447 0.3035 nan nan
2459981 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.662038 -0.271192 0.649812 0.458093 1.126165 1.248619 -0.379113 -1.221970 0.5796 0.5943 0.3735 nan nan
2459980 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.900158 -0.616734 0.225366 -0.153618 0.585345 1.113815 -0.396854 -0.794188 0.6207 0.6323 0.3139 nan nan
2459979 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.702384 -0.455426 0.394654 0.014759 0.637465 -0.092888 -0.564291 -1.169937 0.5716 0.5907 0.3737 nan nan
2459978 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.672946 -0.392004 0.533860 0.193240 0.789150 0.666908 -0.223698 -0.701312 0.5674 0.5840 0.3807 nan nan
2459977 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.480596 -0.211527 0.302785 -0.063337 0.339129 0.498002 -0.127880 -0.987775 0.5394 0.5561 0.3399 nan nan
2459976 not_connected 0.00% 0.00% 0.00% 0.00% - - -0.649256 -0.394232 0.337829 0.043815 1.055314 1.796026 -0.365771 -0.925488 0.5844 0.5998 0.3792 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 22: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 0.719420 -0.561086 -0.135987 0.357510 -0.240208 0.185328 0.719420 -0.464638 -1.090686

Antenna 22: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.944427 -0.937263 -0.594711 -0.004548 -0.765916 0.091784 1.944427 -0.677834 -0.805088

Antenna 22: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected ee Temporal Variability 0.543325 -0.263718 -0.750383 -0.326683 0.270010 0.540591 0.543325 -0.732421 -0.185580

Antenna 22: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 0.669080 -0.708822 -0.345084 0.033926 -0.299280 0.544884 0.669080 -0.250131 -1.217716

Antenna 22: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Shape nan nan nan nan nan nan nan nan nan

Antenna 22: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.938959 -0.594682 -0.248917 0.099047 -0.149850 0.678352 1.938959 -0.779232 -0.855589

Antenna 22: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.355975 -0.566261 -0.417360 0.274532 -0.173963 0.755146 1.355975 -0.817711 -1.698982

Antenna 22: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.342623 -0.575529 -0.276205 -0.016333 -0.572053 -0.263426 1.342623 -0.455168 -0.258556

Antenna 22: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 3.246640 -0.492459 -0.451692 0.221525 -0.320584 1.242681 3.246640 -0.659600 -0.751589

Antenna 22: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.456776 -0.602105 -0.448001 0.297346 -0.156930 0.845497 1.456776 -0.654729 -1.274482

Antenna 22: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.617301 -0.358242 -0.155434 0.663540 0.127999 0.802389 1.617301 -0.774736 -1.133995

Antenna 22: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 0.975016 -0.445465 -0.195997 0.579395 0.191527 0.663453 0.975016 -0.447933 -1.098665

Antenna 22: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.338597 -0.018790 -0.278421 0.327297 0.590227 1.338597 0.794733 -1.021941 -0.098282

Antenna 22: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 0.930089 -0.135343 -0.344197 0.237714 0.694975 0.930089 0.835288 -1.239893 -0.670746

Antenna 22: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.471286 0.080699 -0.413643 0.322872 0.532728 1.471286 0.814273 -0.815043 -0.401942

Antenna 22: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 0.856874 -0.571782 -0.410804 0.350710 -0.107153 0.495137 0.856874 -0.227010 -0.679352

Antenna 22: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.951805 -0.075910 -0.442346 0.121935 0.356695 1.951805 1.374378 -0.941613 0.097330

Antenna 22: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.259608 -0.402051 -0.744239 -0.261942 0.122991 1.259608 0.805063 -1.214986 -0.253812

Antenna 22: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected ee Temporal Discontinuties 0.935849 -0.961198 -0.728946 0.047846 -0.361253 0.512134 -0.312134 0.935849 0.236597

Antenna 22: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.500342 -0.611768 -0.307349 0.435144 0.194522 0.544273 1.500342 -0.035795 -0.773726

Antenna 22: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Shape -0.003960 -0.952877 -0.003960 -0.063595 -0.257072 -0.782483 -0.286629 -0.447041 -0.577362

Antenna 22: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.248619 -0.271192 -0.662038 0.458093 0.649812 1.248619 1.126165 -1.221970 -0.379113

Antenna 22: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.113815 -0.616734 -0.900158 -0.153618 0.225366 1.113815 0.585345 -0.794188 -0.396854

Antenna 22: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected ee Temporal Variability 0.637465 -0.702384 -0.455426 0.394654 0.014759 0.637465 -0.092888 -0.564291 -1.169937

Antenna 22: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected ee Temporal Variability 0.789150 -0.392004 -0.672946 0.193240 0.533860 0.666908 0.789150 -0.701312 -0.223698

Antenna 22: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 0.498002 -0.480596 -0.211527 0.302785 -0.063337 0.339129 0.498002 -0.127880 -0.987775

Antenna 22: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
22 N06 not_connected nn Temporal Variability 1.796026 -0.394232 -0.649256 0.043815 0.337829 1.796026 1.055314 -0.925488 -0.365771
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